Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 

Saved Queries

Sign in to use this feature.

Search Filter Reset All

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
Add Subjects Reset
Select Subjects

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
Add Journals Reset
Select Journals

Article Types

remove_circle_outline
Add Article Types Reset
Select Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
Add Countries / Regions Reset
Select Countries / Regions
Update Search
share announcement

Search Results (3)

Search Parameters:
Authors = Alexander Buslaev

Order results
Result details
Results per page
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
15 pages, 4148 KiB  
Article
Gas-Fueled Binary Energy System with Low-Boiling Working Fluid for Enhanced Power Generation
by Valentin Morenov, Ekaterina Leusheva, Alexander Lavrik, Anna Lavrik and George Buslaev
Energies 2022, 15(7), 2551; https://doi.org/10.3390/en15072551 - 31 Mar 2022
Cited by 10 | Viewed by 2361
Abstract
This article discusses methods of enhanced power generation using a binary power system with low-boiling fluid as an intermediate energy carrier. The binary power system consists of micro-gas and steam power units and is intended for remote standalone power supply. Trifluotrichloroethane was considered [...] Read more.
This article discusses methods of enhanced power generation using a binary power system with low-boiling fluid as an intermediate energy carrier. The binary power system consists of micro-gas and steam power units and is intended for remote standalone power supply. Trifluotrichloroethane was considered as the working agent of the binary cycle. The developed system was modeled by two parts in MATLAB Simulink and Aspen HYSYS. The model in Aspen HYSYS calculates the energy and material balance of the binary energy system. The model in MATLAB Simulink investigates the operation of power electronics in the energy system for quality power generation. The results of the simulation show that the efficiency of power generation in the range of 100 kW in the developed system with micro-turbine power units reaches 50%. Full article
(This article belongs to the Special Issue Recent Progress in Bio-Energy with Carbon Capture and Storage)
►▼ Show Figures

Figure 1

15 pages, 6103 KiB  
Article
Ensuring the Sustainability of Arctic Industrial Facilities under Conditions of Global Climate Change
by George Buslaev, Pavel Tsvetkov, Alexander Lavrik, Andrey Kunshin, Elizaveta Loseva and Dmitry Sidorov
Resources 2021, 10(12), 128; https://doi.org/10.3390/resources10120128 - 15 Dec 2021
Cited by 23 | Viewed by 4551
Abstract
Global climate change poses a challenge to the mineral development industry in the Arctic regions. Civil and industrial buildings designed and constructed without consideration of warming factors are beginning to collapse due to changes in the permafrost structure. St. Petersburg Mining University is [...] Read more.
Global climate change poses a challenge to the mineral development industry in the Arctic regions. Civil and industrial buildings designed and constructed without consideration of warming factors are beginning to collapse due to changes in the permafrost structure. St. Petersburg Mining University is developing technical and technological solutions for the construction of remote Arctic facilities and a methodology for their design based on physical and mathematical predictive modeling. The article presents the results of modeling the thermal regimes of permafrost soils in conditions of thermal influence of piles and proposes measures that allow a timely response to the loss of bearing capacity of piles. Designing pile foundations following the methodology proposed in the article to reduce the risks from global climate change will ensure the stability of remote Arctic facilities located in the zone of permafrost spreading. Full article
(This article belongs to the Special Issue Resource Provision of the Sustainable Development under Global Shocks)
►▼ Show Figures

Figure 1

20 pages, 2877 KiB  
Article
Albumentations: Fast and Flexible Image Augmentations
by Alexander Buslaev, Vladimir I. Iglovikov, Eugene Khvedchenya, Alex Parinov, Mikhail Druzhinin and Alexandr A. Kalinin
Information 2020, 11(2), 125; https://doi.org/10.3390/info11020125 - 24 Feb 2020
Cited by 1717 | Viewed by 61424
Abstract
Data augmentation is a commonly used technique for increasing both the size and the diversity of labeled training sets by leveraging input transformations that preserve corresponding output labels. In computer vision, image augmentations have become a common implicit regularization technique to combat overfitting [...] Read more.
Data augmentation is a commonly used technique for increasing both the size and the diversity of labeled training sets by leveraging input transformations that preserve corresponding output labels. In computer vision, image augmentations have become a common implicit regularization technique to combat overfitting in deep learning models and are ubiquitously used to improve performance. While most deep learning frameworks implement basic image transformations, the list is typically limited to some variations of flipping, rotating, scaling, and cropping. Moreover, image processing speed varies in existing image augmentation libraries. We present Albumentations, a fast and flexible open source library for image augmentation with many various image transform operations available that is also an easy-to-use wrapper around other augmentation libraries. We discuss the design principles that drove the implementation of Albumentations and give an overview of the key features and distinct capabilities. Finally, we provide examples of image augmentations for different computer vision tasks and demonstrate that Albumentations is faster than other commonly used image augmentation tools on most image transform operations. Full article
(This article belongs to the Special Issue Machine Learning with Python)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying article 1-50 on page 1 of 1.
Back to TopTop